Default is to use a total of 4 processors: 4 via shared-memory 1 via Linda Entering Link 1 = C:\G09W\l1.exe PID= 9084. Copyright (c) 1988,1990,1992,1993,1995,1998,2003,2009,2013, Gaussian, Inc. All Rights Reserved. This is part of the Gaussian(R) 09 program. It is based on the Gaussian(R) 03 system (copyright 2003, Gaussian, Inc.), the Gaussian(R) 98 system (copyright 1998, Gaussian, Inc.), the Gaussian(R) 94 system (copyright 1995, Gaussian, Inc.), the Gaussian 92(TM) system (copyright 1992, Gaussian, Inc.), the Gaussian 90(TM) system (copyright 1990, Gaussian, Inc.), the Gaussian 88(TM) system (copyright 1988, Gaussian, Inc.), the Gaussian 86(TM) system (copyright 1986, Carnegie Mellon University), and the Gaussian 82(TM) system (copyright 1983, Carnegie Mellon University). Gaussian is a federally registered trademark of Gaussian, Inc. This software contains proprietary and confidential information, including trade secrets, belonging to Gaussian, Inc. This software is provided under written license and may be used, copied, transmitted, or stored only in accord with that written license. The following legend is applicable only to US Government contracts under FAR: RESTRICTED RIGHTS LEGEND Use, reproduction and disclosure by the US Government is subject to restrictions as set forth in subparagraphs (a) and (c) of the Commercial Computer Software - Restricted Rights clause in FAR 52.227-19. Gaussian, Inc. 340 Quinnipiac St., Bldg. 40, Wallingford CT 06492 --------------------------------------------------------------- Warning -- This program may not be used in any manner that competes with the business of Gaussian, Inc. or will provide assistance to any competitor of Gaussian, Inc. The licensee of this program is prohibited from giving any competitor of Gaussian, Inc. access to this program. By using this program, the user acknowledges that Gaussian, Inc. is engaged in the business of creating and licensing software in the field of computational chemistry and represents and warrants to the licensee that it is not a competitor of Gaussian, Inc. and that it will not use this program in any manner prohibited above. --------------------------------------------------------------- Cite this work as: Gaussian 09, Revision D.01, M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H. P. Hratchian, A. F. Izmaylov, J. Bloino, G. Zheng, J. L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J. A. Montgomery, Jr., J. E. Peralta, F. Ogliaro, M. Bearpark, J. J. Heyd, E. Brothers, K. N. Kudin, V. N. Staroverov, T. Keith, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J. C. Burant, S. S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J. M. Millam, M. Klene, J. E. Knox, J. B. Cross, V. Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R. E. Stratmann, O. Yazyev, A. J. Austin, R. Cammi, C. Pomelli, J. W. Ochterski, R. L. Martin, K. Morokuma, V. G. Zakrzewski, G. A. Voth, P. Salvador, J. J. Dannenberg, S. Dapprich, A. D. Daniels, O. Farkas, J. B. Foresman, J. V. Ortiz, J. Cioslowski, and D. J. Fox, Gaussian, Inc., Wallingford CT, 2013. ****************************************** Gaussian 09: EM64W-G09RevD.01 13-Apr-2013 15-Mar-2014 ****************************************** %rwf=First QST2 cal.rwf %nosave %chk=H:\Physicial computaional\e\First QST2 cal.chk Default route: MaxDisk=10GB ------------------------------------------ # opt=qst2 freq hf/3-21g geom=connectivity ------------------------------------------ 1/5=1,18=20,27=202,38=1,57=2/1,3; 2/9=110,12=2,17=6,18=5,40=1/2; 3/5=5,11=9,16=1,25=1,30=1,71=1/1,2,3; 4//1; 5/5=2,38=5/2; 6/7=2,8=2,9=2,10=2,28=1/1; 7//1,2,3,16; 1/5=1,18=20,27=202/3(2); 2/9=110/2; 99//99; 2/9=110/2; 3/5=5,11=9,16=1,25=1,30=1,71=1/1,2,3; 4/5=5,16=3,69=1/1; 5/5=2,38=5/2; 7//1,2,3,16; 1/5=1,18=20,27=202/3(-5); 2/9=110/2; 6/7=2,8=2,9=2,10=2,19=2,28=1/1; 99/9=1/99; ------------------- Title Card Required ------------------- Symbolic Z-matrix: Charge = 0 Multiplicity = 1 C -4.84669 -0.16602 -0.03954 C -3.72789 -0.52318 -1.04824 H -4.95549 0.92498 0.01894 H -4.53089 -0.50527 0.95774 H -3.61909 -1.61417 -1.10671 H -4.04369 -0.18392 -2.04552 C -6.16841 -0.79013 -0.39467 C -7.28536 -0.11945 -0.67906 H -6.18378 -1.8814 -0.42717 H -8.21069 -0.62841 -0.9359 H -7.31856 0.96841 -0.66156 C -2.40617 0.10093 -0.6931 C -1.28921 -0.56974 -0.40871 H -2.3908 1.19221 -0.66061 H -0.36389 -0.06078 -0.15188 H -1.25602 -1.6576 -0.42621 ------------------- Title Card Required ------------------- Symbolic Z-matrix: Charge = 0 Multiplicity = 1 C -2.46162 -1.64319 1.74526 C -8.45777 -1.19289 1.47491 H -1.53629 -1.13423 2.0021 H -2.42842 -2.73105 1.72776 H -8.49096 -0.10503 1.49241 H -9.38309 -1.70186 1.21808 C -3.57857 -0.97251 1.46087 C -4.90029 -1.59662 1.10574 H -3.5632 0.11876 1.49337 H -4.79149 -2.68762 1.04726 H -5.21609 -1.25737 0.10846 C -7.34081 -1.86357 1.7593 C -6.01909 -1.23946 2.11444 H -7.35618 -2.95485 1.72681 H -5.70329 -1.57872 3.11172 H -6.12789 -0.14847 2.17291 Iteration 1 RMS(Cart)= 0.12651033 RMS(Int)= 1.16778713 Iteration 2 RMS(Cart)= 0.10468286 RMS(Int)= 1.13749230 Iteration 3 RMS(Cart)= 0.08814754 RMS(Int)= 1.11152126 Iteration 4 RMS(Cart)= 0.08167467 RMS(Int)= 1.08872312 Iteration 5 RMS(Cart)= 0.07592404 RMS(Int)= 1.06931315 Iteration 6 RMS(Cart)= 0.06819616 RMS(Int)= 1.05306287 Iteration 7 RMS(Cart)= 0.06360196 RMS(Int)= 1.03961513 Iteration 8 RMS(Cart)= 0.06026620 RMS(Int)= 1.02851632 Iteration 9 RMS(Cart)= 0.05569747 RMS(Int)= 1.01958478 Iteration 10 RMS(Cart)= 0.05168174 RMS(Int)= 1.01214895 Iteration 11 RMS(Cart)= 0.05261192 RMS(Int)= 0.99926153 Iteration 12 RMS(Cart)= 0.04657198 RMS(Int)= 0.99150970 Iteration 13 RMS(Cart)= 0.04474007 RMS(Int)= 0.98633657 Iteration 14 RMS(Cart)= 0.04309410 RMS(Int)= 0.98283793 Iteration 15 RMS(Cart)= 0.04119521 RMS(Int)= 0.97210438 Iteration 16 RMS(Cart)= 0.03867898 RMS(Int)= 0.96567110 Iteration 17 RMS(Cart)= 0.03535741 RMS(Int)= 0.96126537 Iteration 18 RMS(Cart)= 0.03437132 RMS(Int)= 0.95783209 Iteration 19 RMS(Cart)= 0.03329204 RMS(Int)= 0.95518486 Iteration 20 RMS(Cart)= 0.03014150 RMS(Int)= 0.95323453 Iteration 21 RMS(Cart)= 0.00858180 RMS(Int)= 0.95182066 Iteration 22 RMS(Cart)= 0.00660134 RMS(Int)= 0.95067518 Iteration 23 RMS(Cart)= 0.00565391 RMS(Int)= 0.94974257 Iteration 24 RMS(Cart)= 0.00498235 RMS(Int)= 0.94898732 Iteration 25 RMS(Cart)= 0.00443886 RMS(Int)= 0.94838099 Iteration 26 RMS(Cart)= 0.00398493 RMS(Int)= 0.94790029 Iteration 27 RMS(Cart)= 0.00360166 RMS(Int)= 0.94752603 Iteration 28 RMS(Cart)= 0.00327623 RMS(Int)= 0.94724233 Iteration 29 RMS(Cart)= 0.00299901 RMS(Int)= 0.94703591 Iteration 30 RMS(Cart)= 0.00276925 RMS(Int)= 0.94688962 Iteration 31 RMS(Cart)= 0.00258745 RMS(Int)= 0.94679046 Iteration 32 RMS(Cart)= 0.00245120 RMS(Int)= 0.94673138 Iteration 33 RMS(Cart)= 0.00236480 RMS(Int)= 0.94670690 Iteration 34 RMS(Cart)= 0.00227001 RMS(Int)= 0.94671340 Iteration 35 RMS(Cart)= 0.00218218 RMS(Int)= 0.94674753 Iteration 36 RMS(Cart)= 0.00210351 RMS(Int)= 0.94680638 Iteration 37 RMS(Cart)= 0.00203399 RMS(Int)= 0.94688742 Iteration 38 RMS(Cart)= 0.00197310 RMS(Int)= 0.94698844 Iteration 39 RMS(Cart)= 0.00192019 RMS(Int)= 0.94710748 Iteration 40 RMS(Cart)= 0.00188493 RMS(Int)= 0.94723386 Iteration 41 RMS(Cart)= 0.00184144 RMS(Int)= 0.94736862 Iteration 42 RMS(Cart)= 0.00181242 RMS(Int)= 0.94751007 Iteration 43 RMS(Cart)= 0.00182748 RMS(Int)= 0.94765237 Iteration 44 RMS(Cart)= 0.00183857 RMS(Int)= 0.94779512 Iteration 45 RMS(Cart)= 0.00184914 RMS(Int)= 0.94793864 Iteration 46 RMS(Cart)= 0.00186006 RMS(Int)= 0.94808317 Iteration 47 RMS(Cart)= 0.00187146 RMS(Int)= 0.94822892 Iteration 48 RMS(Cart)= 0.00188328 RMS(Int)= 0.94837607 Iteration 49 RMS(Cart)= 0.00189546 RMS(Int)= 0.94852483 Iteration 50 RMS(Cart)= 0.00190793 RMS(Int)= 0.94867540 Iteration 51 RMS(Cart)= 0.00192066 RMS(Int)= 0.94882803 Iteration 52 RMS(Cart)= 0.00193364 RMS(Int)= 0.94898294 Iteration 53 RMS(Cart)= 0.00194685 RMS(Int)= 0.94914039 Iteration 54 RMS(Cart)= 0.00196030 RMS(Int)= 0.94930063 Iteration 55 RMS(Cart)= 0.00197400 RMS(Int)= 0.94946391 Iteration 56 RMS(Cart)= 0.00198795 RMS(Int)= 0.94963051 Iteration 57 RMS(Cart)= 0.00200216 RMS(Int)= 0.94980066 Iteration 58 RMS(Cart)= 0.00201666 RMS(Int)= 0.94997464 Iteration 59 RMS(Cart)= 0.00203144 RMS(Int)= 0.95015268 Iteration 60 RMS(Cart)= 0.00204653 RMS(Int)= 0.95033505 Iteration 61 RMS(Cart)= 0.00206192 RMS(Int)= 0.95052198 Iteration 62 RMS(Cart)= 0.00207764 RMS(Int)= 0.95071372 Iteration 63 RMS(Cart)= 0.00209369 RMS(Int)= 0.95091052 Iteration 64 RMS(Cart)= 0.00211008 RMS(Int)= 0.95111260 Iteration 65 RMS(Cart)= 0.00212681 RMS(Int)= 0.95132019 Iteration 66 RMS(Cart)= 0.00214389 RMS(Int)= 0.95153354 Iteration 67 RMS(Cart)= 0.00216133 RMS(Int)= 0.95175285 Iteration 68 RMS(Cart)= 0.00217914 RMS(Int)= 0.95197836 Iteration 69 RMS(Cart)= 0.00219731 RMS(Int)= 0.95221028 Iteration 70 RMS(Cart)= 0.00221585 RMS(Int)= 0.95244884 Iteration 71 RMS(Cart)= 0.00223477 RMS(Int)= 0.95269423 Iteration 72 RMS(Cart)= 0.00225407 RMS(Int)= 0.95294667 Iteration 73 RMS(Cart)= 0.00227376 RMS(Int)= 0.95320638 Iteration 74 RMS(Cart)= 0.00229384 RMS(Int)= 0.95347356 Iteration 75 RMS(Cart)= 0.00231431 RMS(Int)= 0.95374841 Iteration 76 RMS(Cart)= 0.00230965 RMS(Int)= 0.95403120 Iteration 77 RMS(Cart)= 0.00225040 RMS(Int)= 0.95432272 Iteration 78 RMS(Cart)= 0.00222133 RMS(Int)= 0.95462436 Iteration 79 RMS(Cart)= 0.00220616 RMS(Int)= 0.95493618 Iteration 80 RMS(Cart)= 0.00219812 RMS(Int)= 0.95525819 Iteration 81 RMS(Cart)= 0.00219435 RMS(Int)= 0.95559040 Iteration 82 RMS(Cart)= 0.00219345 RMS(Int)= 0.95593282 Iteration 83 RMS(Cart)= 0.00219458 RMS(Int)= 0.95628544 Iteration 84 RMS(Cart)= 0.00219725 RMS(Int)= 0.95664826 Iteration 85 RMS(Cart)= 0.00220110 RMS(Int)= 0.95702126 Iteration 86 RMS(Cart)= 0.00217465 RMS(Int)= 0.95739130 Iteration 87 RMS(Cart)= 0.00212151 RMS(Int)= 0.95773350 Iteration 88 RMS(Cart)= 0.00205704 RMS(Int)= 0.95807314 Iteration 89 RMS(Cart)= 0.00198789 RMS(Int)= 0.95841451 Iteration 90 RMS(Cart)= 0.00191918 RMS(Int)= 0.95875845 Iteration 91 RMS(Cart)= 0.00185279 RMS(Int)= 0.95910467 Iteration 92 RMS(Cart)= 0.00178911 RMS(Int)= 0.95945258 Iteration 93 RMS(Cart)= 0.00172815 RMS(Int)= 0.95980151 Iteration 94 RMS(Cart)= 0.00166992 RMS(Int)= 0.96015087 Iteration 95 RMS(Cart)= 0.00161440 RMS(Int)= 0.96050009 Iteration 96 RMS(Cart)= 0.00156158 RMS(Int)= 0.96084870 Iteration 97 RMS(Cart)= 0.00151145 RMS(Int)= 0.96119629 Iteration 98 RMS(Cart)= 0.00146395 RMS(Int)= 0.96154251 Iteration 99 RMS(Cart)= 0.00141900 RMS(Int)= 0.96188705 Iteration100 RMS(Cart)= 0.00137649 RMS(Int)= 0.96222964 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.17429574 RMS(Int)= 1.12278709 XScale= 8.43923323 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.17482721 RMS(Int)= 1.05492604 XScale= 4.22669428 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.17702954 RMS(Int)= 1.00116713 XScale= 2.81471497 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.18354339 RMS(Int)= 0.96321202 XScale= 2.09990299 RedQX1 iteration 1 Try 5 RMS(Cart)= 0.20937414 RMS(Int)= 0.94357655 XScale= 1.64748548 RedQX1 iteration 1 Try 6 RMS(Cart)= 0.08682256 RMS(Int)= 0.94349092 XScale= 1.62110199 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.01145916 RMS(Int)= 0.94220088 XScale= 1.62163683 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.01039736 RMS(Int)= 0.94169248 XScale= 1.62552227 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.01155308 RMS(Int)= 0.94118568 XScale= 1.63125399 RedQX1 iteration 2 Try 4 RMS(Cart)= 0.01408808 RMS(Int)= 0.94059978 XScale= 1.63805739 RedQX1 iteration 2 Try 5 RMS(Cart)= 0.02083984 RMS(Int)= 0.93983691 XScale= 1.64578360 RedQX1 iteration 2 Try 6 RMS(Cart)= 0.01223734 RMS(Int)= 0.93949990 XScale= 1.64436207 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.00163040 RMS(Int)= 0.93950639 XScale= 1.64376828 RedQX1 iteration 3 Try 2 RMS(Cart)= 0.00188844 RMS(Int)= 0.93952130 XScale= 1.64320923 RedQX1 iteration 3 Try 3 RMS(Cart)= 0.00231840 RMS(Int)= 0.93954795 XScale= 1.64273945 RedQX1 iteration 3 Try 4 RMS(Cart)= 0.00313251 RMS(Int)= 0.93959309 XScale= 1.64249899 RedQX1 iteration 3 Try 5 RMS(Cart)= 0.00526956 RMS(Int)= 0.93967717 XScale= 1.64303531 RedQX1 iteration 3 Try 6 RMS(Cart)= 0.00353274 RMS(Int)= 0.93970275 XScale= 1.64456772 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.00043897 RMS(Int)= 0.93969654 XScale= 1.64472421 RedQX1 iteration 4 Try 2 RMS(Cart)= 0.00048606 RMS(Int)= 0.93968896 XScale= 1.64485308 RedQX1 iteration 4 Try 3 RMS(Cart)= 0.00056037 RMS(Int)= 0.93967965 XScale= 1.64493219 RedQX1 iteration 4 Try 4 RMS(Cart)= 0.00070032 RMS(Int)= 0.93966791 XScale= 1.64490621 RedQX1 iteration 4 Try 5 RMS(Cart)= 0.00109986 RMS(Int)= 0.93965222 XScale= 1.64456558 RedQX1 iteration 4 Try 6 RMS(Cart)= 0.00085676 RMS(Int)= 0.93965050 XScale= 1.64402006 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.00012399 RMS(Int)= 0.93965125 XScale= 1.64397261 RedQX1 iteration 5 Try 2 RMS(Cart)= 0.00013553 RMS(Int)= 0.93965194 XScale= 1.64392973 RedQX1 iteration 5 Try 3 RMS(Cart)= 0.00015180 RMS(Int)= 0.93965245 XScale= 1.64389584 RedQX1 iteration 5 Try 4 RMS(Cart)= 0.00017823 RMS(Int)= 0.93965245 XScale= 1.64388176 RedQX1 iteration 5 Try 5 RMS(Cart)= 0.00024232 RMS(Int)= 0.93965057 XScale= 1.64392821 RedQX1 iteration 5 Try 6 RMS(Cart)= 0.00015709 RMS(Int)= 0.93964658 XScale= 1.64403556 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.00002668 RMS(Int)= 0.93964608 XScale= 1.64404603 RedQX1 iteration 6 Try 2 RMS(Cart)= 0.00002976 RMS(Int)= 0.93964561 XScale= 1.64405612 RedQX1 iteration 6 Try 3 RMS(Cart)= 0.00003440 RMS(Int)= 0.93964522 XScale= 1.64406535 RedQX1 iteration 6 Try 4 RMS(Cart)= 0.00004265 RMS(Int)= 0.93964504 XScale= 1.64407256 RedQX1 iteration 6 Try 5 RMS(Cart)= 0.00006446 RMS(Int)= 0.93964560 XScale= 1.64407333 RedQX1 iteration 6 Try 6 RMS(Cart)= 0.00004257 RMS(Int)= 0.93964708 XScale= 1.64406171 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00000554 RMS(Int)= 0.93964726 XScale= 1.64406059 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00000598 RMS(Int)= 0.93964743 XScale= 1.64405949 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.00000673 RMS(Int)= 0.93964759 XScale= 1.64405840 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.00000839 RMS(Int)= 0.93964768 XScale= 1.64405731 RedQX1 iteration 7 Try 5 RMS(Cart)= 0.00001415 RMS(Int)= 0.93964758 XScale= 1.64405608 RedQX1 iteration 7 Try 6 RMS(Cart)= 0.00001331 RMS(Int)= 0.93964716 XScale= 1.64405529 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00000183 RMS(Int)= 0.93964710 XScale= 1.64405500 RedQX1 iteration 8 Try 2 RMS(Cart)= 0.00000197 RMS(Int)= 0.93964704 XScale= 1.64405467 RedQX1 iteration 8 Try 3 RMS(Cart)= 0.00000216 RMS(Int)= 0.93964698 XScale= 1.64405428 RedQX1 iteration 8 Try 4 RMS(Cart)= 0.00000252 RMS(Int)= 0.93964694 XScale= 1.64405383 RedQX1 iteration 8 Try 5 RMS(Cart)= 0.00000360 RMS(Int)= 0.93964692 XScale= 1.64405337 RedQX1 iteration 8 Try 6 RMS(Cart)= 0.00000315 RMS(Int)= 0.93964699 XScale= 1.64405377 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00000053 RMS(Int)= 0.93964700 XScale= 1.64405393 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00000059 RMS(Int)= 0.93964701 XScale= 1.64405413 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00000068 RMS(Int)= 0.93964702 XScale= 1.64405437 RedQX1 iteration 9 Try 4 RMS(Cart)= 0.00000084 RMS(Int)= 0.93964703 XScale= 1.64405466 RedQX1 iteration 9 Try 5 RMS(Cart)= 0.00000123 RMS(Int)= 0.93964704 XScale= 1.64405507 RedQX1 iteration 9 Try 6 RMS(Cart)= 0.00000077 RMS(Int)= 0.93964703 XScale= 1.64405509 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00000012 RMS(Int)= 0.93964702 XScale= 1.64405505 RedQX1 iteration 10 Try 2 RMS(Cart)= 0.00000013 RMS(Int)= 0.93964702 XScale= 1.64405500 RedQX1 iteration 10 Try 3 RMS(Cart)= 0.00000016 RMS(Int)= 0.93964702 XScale= 1.64405493 RedQX1 iteration 10 Try 4 RMS(Cart)= 0.00000020 RMS(Int)= 0.93964702 XScale= 1.64405484 RedQX1 iteration 10 Try 5 RMS(Cart)= 0.00000032 RMS(Int)= 0.93964702 XScale= 1.64405469 RedQX1 iteration 10 Try 6 RMS(Cart)= 0.00000022 RMS(Int)= 0.93964703 XScale= 1.64405464 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00000003 RMS(Int)= 0.93964703 XScale= 1.64405464 Iteration 1 RMS(Cart)= 0.12956903 RMS(Int)= 2.11656407 Iteration 2 RMS(Cart)= 0.12767773 RMS(Int)= 2.05793972 Iteration 3 RMS(Cart)= 0.12436539 RMS(Int)= 2.00120265 Iteration 4 RMS(Cart)= 0.12001317 RMS(Int)= 1.94617794 Iteration 5 RMS(Cart)= 0.10835449 RMS(Int)= 1.89416260 Iteration 6 RMS(Cart)= 0.00431357 RMS(Int)= 1.89183817 Iteration 7 RMS(Cart)= 0.00427121 RMS(Int)= 1.88953159 Iteration 8 RMS(Cart)= 0.00423064 RMS(Int)= 1.88724220 Iteration 9 RMS(Cart)= 0.00419183 RMS(Int)= 1.88496936 Iteration 10 RMS(Cart)= 0.00415469 RMS(Int)= 1.88271243 Iteration 11 RMS(Cart)= 0.00411919 RMS(Int)= 1.88047081 Iteration 12 RMS(Cart)= 0.00408528 RMS(Int)= 1.87824390 Iteration 13 RMS(Cart)= 0.00405293 RMS(Int)= 1.87603108 Iteration 14 RMS(Cart)= 0.00402206 RMS(Int)= 1.87383180 Iteration 15 RMS(Cart)= 0.00399266 RMS(Int)= 1.87164549 Iteration 16 RMS(Cart)= 0.00396466 RMS(Int)= 1.86947159 Iteration 17 RMS(Cart)= 0.00393803 RMS(Int)= 1.86730956 Iteration 18 RMS(Cart)= 0.00391272 RMS(Int)= 1.86515887 Iteration 19 RMS(Cart)= 0.00388868 RMS(Int)= 1.86301903 Iteration 20 RMS(Cart)= 0.00386585 RMS(Int)= 1.86088953 Iteration 21 RMS(Cart)= 0.00384421 RMS(Int)= 1.85876990 Iteration 22 RMS(Cart)= 0.00382369 RMS(Int)= 1.85665969 Iteration 23 RMS(Cart)= 0.00380426 RMS(Int)= 1.85455844 Iteration 24 RMS(Cart)= 0.00378585 RMS(Int)= 1.85246575 Iteration 25 RMS(Cart)= 0.00376844 RMS(Int)= 1.85038120 Iteration 26 RMS(Cart)= 0.00375196 RMS(Int)= 1.84830440 Iteration 27 RMS(Cart)= 0.00373639 RMS(Int)= 1.84623499 Iteration 28 RMS(Cart)= 0.00372165 RMS(Int)= 1.84417262 Iteration 29 RMS(Cart)= 0.00370773 RMS(Int)= 1.84211696 Iteration 30 RMS(Cart)= 0.00369455 RMS(Int)= 1.84006768 Iteration 31 RMS(Cart)= 0.00368208 RMS(Int)= 1.83802450 Iteration 32 RMS(Cart)= 0.00367027 RMS(Int)= 1.83598714 Iteration 33 RMS(Cart)= 0.00365905 RMS(Int)= 1.83395533 Iteration 34 RMS(Cart)= 0.00364836 RMS(Int)= 1.83192883 Iteration 35 RMS(Cart)= 0.00363812 RMS(Int)= 1.82990739 Iteration 36 RMS(Cart)= 0.00362820 RMS(Int)= 1.82789075 Iteration 37 RMS(Cart)= 0.00361840 RMS(Int)= 1.82587852 Iteration 38 RMS(Cart)= 0.00360832 RMS(Int)= 1.82386961 Iteration 39 RMS(Cart)= 0.00359658 RMS(Int)= 1.82185052 Iteration 40 RMS(Cart)= 0.00356899 RMS(Int)= 1.84173327 Iteration 41 RMS(Cart)= 0.09041324 RMS(Int)= 1.78717239 Iteration 42 RMS(Cart)= 0.07993470 RMS(Int)= 1.72126495 Iteration 43 RMS(Cart)= 0.05948796 RMS(Int)= 1.67130809 Iteration 44 RMS(Cart)= 0.00993773 RMS(Int)= 1.66344765 Iteration 45 RMS(Cart)= 0.00866767 RMS(Int)= 1.65656263 Iteration 46 RMS(Cart)= 0.00807553 RMS(Int)= 1.65011733 Iteration 47 RMS(Cart)= 0.00761746 RMS(Int)= 1.64400948 Iteration 48 RMS(Cart)= 0.00724226 RMS(Int)= 1.63817613 Iteration 49 RMS(Cart)= 0.00687688 RMS(Int)= 1.63260937 Iteration 50 RMS(Cart)= 0.00653146 RMS(Int)= 1.62728739 Iteration 51 RMS(Cart)= 0.00621722 RMS(Int)= 1.62218046 Iteration 52 RMS(Cart)= 0.00595100 RMS(Int)= 1.61725150 Iteration 53 RMS(Cart)= 0.00575317 RMS(Int)= 1.61244975 Iteration 54 RMS(Cart)= 0.00559894 RMS(Int)= 1.60774546 Iteration 55 RMS(Cart)= 0.00548033 RMS(Int)= 1.60311461 Iteration 56 RMS(Cart)= 0.00540695 RMS(Int)= 1.59852093 Iteration 57 RMS(Cart)= 0.00538066 RMS(Int)= 1.59392502 Iteration 58 RMS(Cart)= 0.00540760 RMS(Int)= 1.58928043 Iteration 59 RMS(Cart)= 0.00548710 RMS(Int)= 1.58453913 Iteration 60 RMS(Cart)= 0.00542803 RMS(Int)= 1.57982232 Iteration 61 RMS(Cart)= 0.00427894 RMS(Int)= 1.57610759 Iteration 62 RMS(Cart)= 0.00267907 RMS(Int)= 1.57379197 Iteration 63 RMS(Cart)= 0.00212582 RMS(Int)= 1.57195464 Iteration 64 RMS(Cart)= 0.00194832 RMS(Int)= 1.57026542 Iteration 65 RMS(Cart)= 0.00186072 RMS(Int)= 1.56864255 Iteration 66 RMS(Cart)= 0.00179752 RMS(Int)= 1.56706078 Iteration 67 RMS(Cart)= 0.00173761 RMS(Int)= 1.56551832 Iteration 68 RMS(Cart)= 0.00168434 RMS(Int)= 1.56400993 Iteration 69 RMS(Cart)= 0.00165124 RMS(Int)= 1.56251718 Iteration 70 RMS(Cart)= 0.00164093 RMS(Int)= 1.56101726 Iteration 71 RMS(Cart)= 0.00163240 RMS(Int)= 1.55950236 Iteration 72 RMS(Cart)= 0.00161860 RMS(Int)= 1.55795868 Iteration 73 RMS(Cart)= 0.00159682 RMS(Int)= 1.55624977 Iteration 74 RMS(Cart)= 0.00155212 RMS(Int)= 1.57065318 Iteration 75 RMS(Cart)= 0.00253803 RMS(Int)= 1.56815948 Iteration 76 RMS(Cart)= 0.00190208 RMS(Int)= 1.56629326 Iteration 77 RMS(Cart)= 0.00192437 RMS(Int)= 1.56439469 Iteration 78 RMS(Cart)= 0.00194626 RMS(Int)= 1.56246320 Iteration 79 RMS(Cart)= 0.00195290 RMS(Int)= 1.56051397 Iteration 80 RMS(Cart)= 0.00194183 RMS(Int)= 1.55856544 Iteration 81 RMS(Cart)= 0.00191931 RMS(Int)= 1.55663016 Iteration 82 RMS(Cart)= 0.00188899 RMS(Int)= 1.55471728 Iteration 83 RMS(Cart)= 0.00184809 RMS(Int)= 1.55283894 Iteration 84 RMS(Cart)= 0.00177600 RMS(Int)= 1.55102862 Iteration 85 RMS(Cart)= 0.00164630 RMS(Int)= 1.54934477 Iteration 86 RMS(Cart)= 0.00153618 RMS(Int)= 1.54776694 Iteration 87 RMS(Cart)= 0.00146713 RMS(Int)= 1.54625448 Iteration 88 RMS(Cart)= 0.00142319 RMS(Int)= 1.54478273 Iteration 89 RMS(Cart)= 0.00139099 RMS(Int)= 1.54334078 Iteration 90 RMS(Cart)= 0.00088411 RMS(Int)= 1.54242221 Iteration 91 RMS(Cart)= 0.00087473 RMS(Int)= 1.54151221 Iteration 92 RMS(Cart)= 0.00086606 RMS(Int)= 1.54061047 Iteration 93 RMS(Cart)= 0.00085787 RMS(Int)= 1.53971707 Iteration 94 RMS(Cart)= 0.00084985 RMS(Int)= 1.53883269 Iteration 95 RMS(Cart)= 0.00084196 RMS(Int)= 1.53795868 Iteration 96 RMS(Cart)= 0.00083391 RMS(Int)= 1.53709823 Iteration 97 RMS(Cart)= 0.00082545 RMS(Int)= 1.53626016 Iteration 98 RMS(Cart)= 0.00081624 RMS(Int)= 1.53549012 Iteration 99 RMS(Cart)= 0.00080037 RMS(Int)= 1.54640831 Iteration100 RMS(Cart)= 0.00142936 RMS(Int)= 1.54436733 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.41550081 RMS(Int)= 1.96734806 XScale= 6.86384079 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.41368701 RMS(Int)= 1.78065907 XScale= 3.25832868 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.41341446 RMS(Int)= 1.66717706 XScale= 1.91353033 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.47593016 RMS(Int)= 2.11601851 XScale= 1.24613168 RedQX1 iteration 1 Try 5 RMS(Cart)= 1.23684366 RMS(Int)= 2.64244589 XScale= 1.19595461 RedQX1 iteration 1 Try 6 RMS(Cart)= 1.97745102 RMS(Int)= 3.46146007 XScale= 0.93311974 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.39549020 RMS(Int)= 2.73257444 XScale= 1.17974408 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.57118306 RMS(Int)= 2.89174984 XScale= 1.11441140 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.85655129 RMS(Int)= 3.31889336 XScale= 0.92586204 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.51393078 RMS(Int)= 3.10838735 XScale= 1.00401744 RedQX1 iteration 3 Try 2 RMS(Cart)= 0.76979030 RMS(Int)= 3.59457231 XScale= 0.83880717 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.61583224 RMS(Int)= 3.49053941 XScale= 0.87082579 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.12316645 RMS(Int)= 3.17964842 XScale= 0.97742348 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.02463329 RMS(Int)= 3.12239235 XScale= 0.99873620 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00492666 RMS(Int)= 3.11117800 XScale= 1.00296309 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00494121 RMS(Int)= 3.11398154 XScale= 1.00190496 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.00495583 RMS(Int)= 3.11679800 XScale= 1.00084304 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.00497052 RMS(Int)= 3.11962746 XScale= 0.99977735 RedQX1 iteration 7 Try 5 RMS(Cart)= 0.00498528 RMS(Int)= 3.12246996 XScale= 0.99870788 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00495338 RMS(Int)= 3.12245176 XScale= 0.99871473 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00099068 RMS(Int)= 3.12019191 XScale= 0.99956490 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00099126 RMS(Int)= 3.12075687 XScale= 0.99935230 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00099185 RMS(Int)= 3.12132235 XScale= 0.99913955 RedQX1 iteration 9 Try 4 RMS(Cart)= 0.00099243 RMS(Int)= 3.12188835 XScale= 0.99892664 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00099148 RMS(Int)= 3.12188780 XScale= 0.99892685 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00019830 RMS(Int)= 3.12143542 XScale= 0.99909701 RedQX1 iteration 11 Try 2 RMS(Cart)= 0.00019832 RMS(Int)= 3.12154852 XScale= 0.99905447 RedQX1 iteration 11 Try 3 RMS(Cart)= 0.00019834 RMS(Int)= 3.12166163 XScale= 0.99901192 RedQX1 iteration 11 Try 4 RMS(Cart)= 0.00019837 RMS(Int)= 3.12177477 XScale= 0.99896936 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00019833 RMS(Int)= 3.12177475 XScale= 0.99896937 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00003967 RMS(Int)= 3.12168426 XScale= 0.99900341 RedQX1 iteration 13 Try 2 RMS(Cart)= 0.00003967 RMS(Int)= 3.12170688 XScale= 0.99899490 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00003967 RMS(Int)= 3.12170688 XScale= 0.99899490 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000793 RMS(Int)= 3.12168878 XScale= 0.99900171 RedQX1 iteration 15 Try 2 RMS(Cart)= 0.00000793 RMS(Int)= 3.12169331 XScale= 0.99900001 RedQX1 iteration 15 Try 3 RMS(Cart)= 0.00000793 RMS(Int)= 3.12169783 XScale= 0.99899830 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000793 RMS(Int)= 3.12169783 XScale= 0.99899830 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000159 RMS(Int)= 3.12169421 XScale= 0.99899967 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000032 RMS(Int)= 3.12169349 XScale= 0.99899994 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000006 RMS(Int)= 3.12169334 XScale= 0.99899999 RedQX1 iteration 20 Try 1 RMS(Cart)= 0.00000001 RMS(Int)= 3.12169331 XScale= 0.99900000 Iteration 1 RMS(Cart)= 0.31937436 RMS(Int)= 2.84272664 Iteration 2 RMS(Cart)= 0.32469873 RMS(Int)= 2.75390891 Iteration 3 RMS(Cart)= 0.29855130 RMS(Int)= 2.66957245 Iteration 4 RMS(Cart)= 0.27299343 RMS(Int)= 2.59139018 Iteration 5 RMS(Cart)= 0.24426406 RMS(Int)= 2.51957757 Iteration 6 RMS(Cart)= 0.23435405 RMS(Int)= 2.45065675 Iteration 7 RMS(Cart)= 0.18348286 RMS(Int)= 2.39448660 Iteration 8 RMS(Cart)= 0.00732304 RMS(Int)= 2.39188838 Iteration 9 RMS(Cart)= 0.00726381 RMS(Int)= 2.38931149 Iteration 10 RMS(Cart)= 0.00403476 RMS(Int)= 2.38787852 Iteration 11 RMS(Cart)= 0.00407588 RMS(Int)= 2.38643127 Iteration 12 RMS(Cart)= 0.00411588 RMS(Int)= 2.38497021 Iteration 13 RMS(Cart)= 0.00300978 RMS(Int)= 2.38390160 Iteration 14 RMS(Cart)= 0.00304700 RMS(Int)= 2.38282005 Iteration 15 RMS(Cart)= 0.00308371 RMS(Int)= 2.38172576 Iteration 16 RMS(Cart)= 0.00312002 RMS(Int)= 2.38061891 Iteration 17 RMS(Cart)= 0.00315609 RMS(Int)= 2.37949960 Iteration 18 RMS(Cart)= 0.00319207 RMS(Int)= 2.37836789 Iteration 19 RMS(Cart)= 0.00322816 RMS(Int)= 2.37722378 Iteration 20 RMS(Cart)= 0.00326466 RMS(Int)= 2.37606713 Iteration 21 RMS(Cart)= 0.00330199 RMS(Int)= 2.37489767 Iteration 22 RMS(Cart)= 0.00333479 RMS(Int)= 2.37371667 Iteration 23 RMS(Cart)= 0.00336142 RMS(Int)= 2.37252592 Iteration 24 RMS(Cart)= 0.00339441 RMS(Int)= 2.37132352 Iteration 25 RMS(Cart)= 0.00343901 RMS(Int)= 2.37010536 Iteration 26 RMS(Cart)= 0.00350509 RMS(Int)= 2.36886383 Iteration 27 RMS(Cart)= 0.00357818 RMS(Int)= 2.36759645 Iteration 28 RMS(Cart)= 0.00355424 RMS(Int)= 2.36633750 Iteration 29 RMS(Cart)= 0.00350573 RMS(Int)= 2.36509566 Iteration 30 RMS(Cart)= 0.00348207 RMS(Int)= 2.36386212 Iteration 31 RMS(Cart)= 0.00347190 RMS(Int)= 2.36263209 Iteration 32 RMS(Cart)= 0.00346795 RMS(Int)= 2.36140335 Iteration 33 RMS(Cart)= 0.00346687 RMS(Int)= 2.36017486 Iteration 34 RMS(Cart)= 0.00346695 RMS(Int)= 2.35894618 Iteration 35 RMS(Cart)= 0.00346722 RMS(Int)= 2.35771721 Iteration 36 RMS(Cart)= 0.00346704 RMS(Int)= 2.35648810 Iteration 37 RMS(Cart)= 0.00346596 RMS(Int)= 2.35525914 Iteration 38 RMS(Cart)= 0.00346356 RMS(Int)= 2.35403076 Iteration 39 RMS(Cart)= 0.00345951 RMS(Int)= 2.35280352 Iteration 40 RMS(Cart)= 0.00345195 RMS(Int)= 2.35157889 Iteration 41 RMS(Cart)= 0.00344050 RMS(Int)= 2.35035825 Iteration 42 RMS(Cart)= 0.00342493 RMS(Int)= 2.34914304 Iteration 43 RMS(Cart)= 0.00340506 RMS(Int)= 2.34793476 Iteration 44 RMS(Cart)= 0.00338101 RMS(Int)= 2.34673487 Iteration 45 RMS(Cart)= 0.00335328 RMS(Int)= 2.34554468 Iteration 46 RMS(Cart)= 0.00332266 RMS(Int)= 2.34436521 Iteration 47 RMS(Cart)= 0.00328989 RMS(Int)= 2.34319775 Iteration 48 RMS(Cart)= 0.00325257 RMS(Int)= 2.35153938 Iteration 49 RMS(Cart)= 0.00511340 RMS(Int)= 2.35002470 Iteration 50 RMS(Cart)= 0.00516311 RMS(Int)= 2.34849777 Iteration 51 RMS(Cart)= 0.00521141 RMS(Int)= 2.34695588 Iteration 52 RMS(Cart)= 0.00524756 RMS(Int)= 2.34540166 Iteration 53 RMS(Cart)= 0.00526519 RMS(Int)= 2.34384016 Iteration 54 RMS(Cart)= 0.00526433 RMS(Int)= 2.34227660 Iteration 55 RMS(Cart)= 0.00524898 RMS(Int)= 2.34071517 Iteration 56 RMS(Cart)= 0.00522372 RMS(Int)= 2.33915875 Iteration 57 RMS(Cart)= 0.00519221 RMS(Int)= 2.33760918 Iteration 58 RMS(Cart)= 0.00515700 RMS(Int)= 2.33606757 Iteration 59 RMS(Cart)= 0.00511978 RMS(Int)= 2.33453456 Iteration 60 RMS(Cart)= 0.00508162 RMS(Int)= 2.33301045 Iteration 61 RMS(Cart)= 0.00504394 RMS(Int)= 2.33149512 Iteration 62 RMS(Cart)= 0.00354001 RMS(Int)= 2.33042868 Iteration 63 RMS(Cart)= 0.00352948 RMS(Int)= 2.32936416 Iteration 64 RMS(Cart)= 0.00351875 RMS(Int)= 2.32830163 Iteration 65 RMS(Cart)= 0.00350788 RMS(Int)= 2.32724113 Iteration 66 RMS(Cart)= 0.00349694 RMS(Int)= 2.32618270 Iteration 67 RMS(Cart)= 0.00348596 RMS(Int)= 2.32512635 Iteration 68 RMS(Cart)= 0.00347499 RMS(Int)= 2.32407209 Iteration 69 RMS(Cart)= 0.00346404 RMS(Int)= 2.32301992 Iteration 70 RMS(Cart)= 0.00345317 RMS(Int)= 2.32196982 Iteration 71 RMS(Cart)= 0.00344234 RMS(Int)= 2.32092179 Iteration 72 RMS(Cart)= 0.00343161 RMS(Int)= 2.31987581 Iteration 73 RMS(Cart)= 0.00342097 RMS(Int)= 2.31883185 Iteration 74 RMS(Cart)= 0.00341045 RMS(Int)= 2.31778989 Iteration 75 RMS(Cart)= 0.00340000 RMS(Int)= 2.31674990 Iteration 76 RMS(Cart)= 0.00338969 RMS(Int)= 2.31571186 Iteration 77 RMS(Cart)= 0.00337949 RMS(Int)= 2.31467574 Iteration 78 RMS(Cart)= 0.00336941 RMS(Int)= 2.31364149 Iteration 79 RMS(Cart)= 0.00335946 RMS(Int)= 2.31260910 Iteration 80 RMS(Cart)= 0.00334963 RMS(Int)= 2.31157853 Iteration 81 RMS(Cart)= 0.00333992 RMS(Int)= 2.31054974 Iteration 82 RMS(Cart)= 0.00333036 RMS(Int)= 2.30952270 Iteration 83 RMS(Cart)= 0.00332092 RMS(Int)= 2.30849736 Iteration 84 RMS(Cart)= 0.00331161 RMS(Int)= 2.30747370 Iteration 85 RMS(Cart)= 0.00330242 RMS(Int)= 2.30645168 Iteration 86 RMS(Cart)= 0.00329335 RMS(Int)= 2.30543127 Iteration 87 RMS(Cart)= 0.00328444 RMS(Int)= 2.30441241 Iteration 88 RMS(Cart)= 0.00327565 RMS(Int)= 2.30339508 Iteration 89 RMS(Cart)= 0.00248795 RMS(Int)= 2.30262101 Iteration 90 RMS(Cart)= 0.00074164 RMS(Int)= 2.30238975 Iteration 91 RMS(Cart)= 0.00074041 RMS(Int)= 2.30215882 Iteration 92 RMS(Cart)= 0.00073917 RMS(Int)= 2.30192821 Iteration 93 RMS(Cart)= 0.00073793 RMS(Int)= 2.30169792 Iteration 94 RMS(Cart)= 0.00073668 RMS(Int)= 2.30146796 Iteration 95 RMS(Cart)= 0.00073542 RMS(Int)= 2.30123833 Iteration 96 RMS(Cart)= 0.00073415 RMS(Int)= 2.30100904 Iteration 97 RMS(Cart)= 0.00073288 RMS(Int)= 2.30078008 Iteration 98 RMS(Cart)= 0.00073160 RMS(Int)= 2.30055146 Iteration 99 RMS(Cart)= 0.00073031 RMS(Int)= 2.30032318 Iteration100 RMS(Cart)= 0.00072901 RMS(Int)= 2.30009525 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.81326094 RMS(Int)= 2.51178716 XScale= 6.03584958 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.81616071 RMS(Int)= 2.28142289 XScale= 3.23408385 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.88276777 RMS(Int)= 2.44640161 XScale= 2.02886870 RedQX1 iteration 1 Try 4 RMS(Cart)= 1.31180092 RMS(Int)= 3.01032319 XScale= 1.47239578 RedQX1 iteration 1 Try 5 RMS(Cart)= 3.48658940 RMS(Int)= 5.87620318 XScale= 0.75010951 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.69731788 RMS(Int)= 3.53149627 XScale= 1.34470117 RedQX1 iteration 2 Try 2 RMS(Cart)= 1.03000539 RMS(Int)= 4.24897185 XScale= 1.10100598 RedQX1 iteration 2 Try 3 RMS(Cart)= 1.70375880 RMS(Int)= 5.57225066 XScale= 0.78855145 RedQX1 iteration 3 Try 1 RMS(Cart)= 1.02225528 RMS(Int)= 5.03575088 XScale= 0.90212600 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.20445106 RMS(Int)= 4.39113454 XScale= 1.05908925 RedQX1 iteration 4 Try 2 RMS(Cart)= 0.21812195 RMS(Int)= 4.59510487 XScale= 1.01531405 RedQX1 iteration 4 Try 3 RMS(Cart)= 0.23242316 RMS(Int)= 4.76344847 XScale= 0.96698501 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.21382931 RMS(Int)= 4.74978012 XScale= 0.97077887 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.04276586 RMS(Int)= 4.62565395 XScale= 1.00628223 RedQX1 iteration 6 Try 2 RMS(Cart)= 0.04332548 RMS(Int)= 4.65678194 XScale= 0.99720099 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.04297887 RMS(Int)= 4.65653212 XScale= 0.99727339 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00859577 RMS(Int)= 4.63181367 XScale= 1.00447558 RedQX1 iteration 8 Try 2 RMS(Cart)= 0.00861817 RMS(Int)= 4.63799650 XScale= 1.00266700 RedQX1 iteration 8 Try 3 RMS(Cart)= 0.00864067 RMS(Int)= 4.64420252 XScale= 1.00085649 RedQX1 iteration 8 Try 4 RMS(Cart)= 0.00866329 RMS(Int)= 4.65043182 XScale= 0.99904410 RedQX1 iteration 8 Try 5 RMS(Cart)= 0.00868602 RMS(Int)= 4.65668449 XScale= 0.99722984 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00863043 RMS(Int)= 4.65664444 XScale= 0.99724144 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00172609 RMS(Int)= 4.65167371 XScale= 0.99868337 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00034522 RMS(Int)= 4.65068017 XScale= 0.99897194 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00006904 RMS(Int)= 4.65048149 XScale= 0.99902967 RedQX1 iteration 12 Try 2 RMS(Cart)= 0.00006904 RMS(Int)= 4.65053116 XScale= 0.99901524 RedQX1 iteration 12 Try 3 RMS(Cart)= 0.00006905 RMS(Int)= 4.65058083 XScale= 0.99900080 RedQX1 iteration 12 Try 4 RMS(Cart)= 0.00006905 RMS(Int)= 4.65063051 XScale= 0.99898637 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00006905 RMS(Int)= 4.65063050 XScale= 0.99898637 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00001381 RMS(Int)= 4.65059077 XScale= 0.99899792 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000276 RMS(Int)= 4.65058282 XScale= 0.99900023 RedQX1 iteration 15 Try 2 RMS(Cart)= 0.00000276 RMS(Int)= 4.65058481 XScale= 0.99899965 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000276 RMS(Int)= 4.65058481 XScale= 0.99899965 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000055 RMS(Int)= 4.65058322 XScale= 0.99900011 RedQX1 iteration 17 Try 2 RMS(Cart)= 0.00000055 RMS(Int)= 4.65058361 XScale= 0.99900000 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000055 RMS(Int)= 4.65058361 XScale= 0.99900000 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058330 XScale= 0.99900009 RedQX1 iteration 19 Try 2 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058337 XScale= 0.99900007 RedQX1 iteration 19 Try 3 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058345 XScale= 0.99900004 RedQX1 iteration 19 Try 4 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058353 XScale= 0.99900002 RedQX1 iteration 19 Try 5 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058361 XScale= 0.99900000 RedQX1 iteration 20 Try 1 RMS(Cart)= 0.00000011 RMS(Int)= 4.65058361 XScale= 0.99900000 Old curvilinear step not converged, using linear step: SCX= 1.51D+01 DXMaxT= 1.25-314 SCLim= 6.24-315 Fact= 4.14-316 RedCar/ORedCr failed for GTrans. Error termination via Lnk1e in C:\G09W\l101.exe at Sat Mar 15 23:08:14 2014. Job cpu time: 0 days 0 hours 0 minutes 1.0 seconds. File lengths (MBytes): RWF= 5 Int= 0 D2E= 0 Chk= 1 Scr= 1